Covid Report for Family

Background

Notes and format last updated Apr 16, 2020

• This page shows COVID data broken down into regions that affect our family. It pulls from publicly available raw data from the NY Times, which is reported daily. It’s on a one-day lag, so when you see this report, the most recent day included will be that reported the day prior.
• The table of contents above summarizes the major sections and can be used to jump to those sections.
• Each major section is then divided into tabs to allow you to more easily shuffle between geographies and metrics.
  • If you open on your phone, I don’t believe the tabs will work, so you’ll just see the page as one long, continuous document.
• More detailed descriptions and context can be found in each section.

Growth rates

Heat maps

• The two heat maps below compare how quickly total cases or deaths have grown at various times in our respective geopgraphies.
• The first plot compares growth rate for total cases; the second, growth rate for total deaths.
• The metric used is doubling time, by which I mean how quickly total cases or deaths are doubling.
• The plots track that doubling time at each date for our geographies. Darker colors reflect shorter doubling times, and thus periods of faster growth.
  • You can use the plots to track each geography over time and to compare the geographies to one another.
  • You can also compare the cases and death charts, to see how faster periods of death growth follow faster periods of case growth.

Case growth rates

• This section charts the growth rate of both total and new cases for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total cases and new cases.
  • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
• Note that we’re charting growth rate and not a count of cases, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new cases) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
• Each of these two lines using rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new case reporting at the state level.
  • For total cases, the trendlines are a rolling 3-day average of daily growth rates in total cases. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total cases have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total case line get as close to zero as possible.
  • For new cases, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new cases. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total cases, we want to watch for the lines for new cases to get consistently below zero and stay there. That means that we are consistently seeing fewer new cases on a daily basis.

U.S.

Our states

Death growth rates

• This section charts the growth rate of both total and new cases for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total cases and new cases.
  • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
• Note that we’re charting growth rate and not a count of deaths, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new deaths) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
• Each of these two lines using rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new death reporting at the state level.
  • For total deaths, the trendlines are a rolling 3-day average of daily growth rates in total deaths. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total deaths have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total death line get as close to zero as possible.
  • For new deaths, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new deaths. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total deaths, we want to watch for the lines for new deaths to get consistently below zero and stay there. That means that we are consistently seeing fewer new deaths on a daily basis.

U.S.

Our states

By population rankings

This section tracks metrics for states and counties normalized for population (number of cases or deaths per million residents), and then compares these figures both for our geographies and the country overall.

States

• This section shows tables ranking all 50 states for per populations rates of total cases, new cases, total deaths, and new deaths.
• For each metric, in addition to the tables, the trends for the top states are plotted over time.
  • We only plot the top ten states for each metric so that the plots aren’t too crowded. But you can view the full 50-state rankings in the tables.

Total confirmed cases

Table of total confirmed cases per million residents (all 50 states)

Ranking	State	Cases Per Million
1	New York	14,808
2	New Jersey	12,276
3	Massachusetts	7,970
4	Connecticut	7,087
5	Rhode Island	7,022
6	Louisiana	5,759
7	District of Columbia	5,442
8	Delaware	4,142
9	Michigan	3,780
10	Illinois	3,464
11	Pennsylvania	3,336
12	Maryland	3,073
13	South Dakota	2,501
14	Colorado	2,334
15	Indiana	2,229
16	Georgia	2,115
17	Mississippi	1,986
18	Washington	1,794
19	Iowa	1,740
20	Nebraska	1,615
21	Virginia	1,519
22	Nevada	1,505
23	Florida	1,467
24	Tennessee	1,390
25	New Hampshire	1,370
26	Ohio	1,365
27	Vermont	1,363
28	Alabama	1,309
29	New Mexico	1,301
30	Utah	1,286
31	Missouri	1,140
32	North Dakota	1,137
33	California	1,105
34	Kansas	1,094
35	South Carolina	1,066
36	Wisconsin	1,015
37	Arkansas	994
38	Idaho	989
39	Kentucky	911
40	Arizona	896
41	Texas	869
42	North Carolina	841
43	Oklahoma	822
44	Maine	755
45	Wyoming	641
46	Minnesota	638
47	West Virginia	587
48	Oregon	547
49	Alaska	463
50	Puerto Rico	429
51	Hawaii	423
52	Montana	419

New confirmed cases

Table of new cases per million residents: rolling 3-day average (all 50 states)

Ranking	State	New Cases Per Million
1	Massachusetts	431
2	New York	421
3	Rhode Island	372
4	New Jersey	339
5	Delaware	248
6	District of Columbia	226
7	Connecticut	202
8	Illinois	183
9	Iowa	163
10	Nebraska	161
11	Maryland	156
12	Colorado	126
13	Pennsylvania	113
14	Indiana	97
15	South Dakota	96
16	Mississippi	84
17	Michigan	83
18	Virginia	76
19	Louisiana	74
20	North Dakota	69
21	Kansas	65
22	Tennessee	61
23	New Mexico	55
24	Utah	52
25	Wisconsin	49
26	Georgia	48
27	New Hampshire	47
28	Nevada	46
29	Arkansas	44
30	Alabama	40
31	Kentucky	39
32	Minnesota	39
33	North Carolina	38
34	South Carolina	37
35	Missouri	36
36	Ohio	36
37	California	35
38	Arizona	34
39	Washington	33
40	Florida	29
41	Texas	28
42	Wyoming	22
43	Maine	19
44	Oklahoma	19
45	Oregon	14
46	Puerto Rico	14
47	Vermont	13
48	West Virginia	13
49	Idaho	8
50	Hawaii	2
51	Alaska	1
52	Montana	1

Total deaths

Table of total deaths per million residents (all 50 states)

Ranking	State	Deaths Per Million
1	New York	872
2	New Jersey	668
3	Connecticut	539
4	Massachusetts	420
5	Louisiana	359
6	Michigan	331
7	District of Columbia	252
8	Rhode Island	213
9	Illinois	153
10	Pennsylvania	146
11	Maryland	136
12	Delaware	123
13	Indiana	120
14	Colorado	117
15	Washington	99
16	Georgia	85
17	Mississippi	76
18	Vermont	73
19	Nevada	66
20	Ohio	62
21	Virginia	52
22	Florida	49
23	Oklahoma	49
24	Minnesota	48
25	Kentucky	47
26	New Mexico	47
27	Wisconsin	47
28	Missouri	45
29	Alabama	44
30	New Hampshire	44
31	California	43
32	Kansas	41
33	Arizona	38
34	Iowa	37
35	Maine	37
36	South Carolina	33
37	Idaho	31
38	North Carolina	29
39	Nebraska	28
40	Tennessee	27
41	Texas	23
42	North Dakota	22
43	Oregon	21
44	West Virginia	18
45	Arkansas	16
46	Puerto Rico	16
47	Montana	13
48	South Dakota	12
49	Utah	12
50	Wyoming	12
51	Alaska	9
52	Hawaii	9

New deaths

Table of new deaths per million residents: rolling 3-day average (all 50 states)

Ranking	State	New Deaths Per Million
1	Connecticut	26
2	Massachusetts	26
3	New Jersey	21
4	New York	21
5	District of Columbia	18
6	Michigan	11
7	Rhode Island	11
8	Delaware	9
9	Louisiana	9
10	Maryland	8
11	Colorado	7
12	Illinois	6
13	Indiana	5
14	Minnesota	4
15	New Mexico	3
16	Pennsylvania	3
17	Iowa	2
18	Mississippi	2
19	New Hampshire	2
20	Ohio	2
21	Virginia	2
22	Alabama	1
23	California	1
24	Florida	1
25	Georgia	1
26	Kentucky	1
27	Maine	1
28	Missouri	1
29	Nebraska	1
30	Nevada	1
31	North Carolina	1
32	Oklahoma	1
33	South Carolina	1
34	Vermont	1
35	Washington	1
36	Alaska	0
37	Arizona	0
38	Arkansas	0
39	Hawaii	0
40	Idaho	0
41	Kansas	0
42	Montana	0
43	North Dakota	0
44	Oregon	0
45	Puerto Rico	0
46	South Dakota	0
47	Tennessee	0
48	Texas	0
49	Utah	0
50	West Virginia	0
51	Wisconsin	0
52	Wyoming	0

Counties

• This section focuses on the county level. It shows tables with our counties ranked by percentile of U.S. counties for per population rates of total cases and total deaths.
  • Each table also shows the top five counties in the country in addition to our counties, for added perspecive.
• In addition to the tables, our counties’ percentile for both total cases and total deaths are plotted over time.

Confirmed cases

Table showing total cases per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.

County	State	Cases Per Million	Raw Ranking	Percentile
New York	New York	97,174	1	99
Lincoln	Arkansas	55,820	2	99
Bledsoe	Tennessee	39,033	3	99
Rockland	New York	34,550	4	99
Marion	Ohio	33,460	5	99
Davidson	Tennessee	3,414	208	93
Richland	South Carolina	2,013	427	86
Pierce	Washington	1,466	614	80
Orange	California	653	1264	59
York	South Carolina	644	1279	59

Our county percentiles over time

Deaths

Table showing total deaths per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.

County	State	Deaths Per Million	Raw Ranking	Percentile
New York	New York	7,152	1	99
Randolph	Georgia	2,803	2	99
Terrell	Georgia	1,993	3	99
Early	Georgia	1,472	4	99
Nassau	New York	1,446	5	99
Pierce	Washington	53	660	78
Richland	South Carolina	46	742	76
Davidson	Tennessee	33	892	71
Orange	California	12	1237	60
York	South Carolina	11	1260	59

Our county percentiles over time

Raw counts

• This section shows the raw counts over time for the U.S., our states, and our counties for four categories:
  • Total confirmed cases: This is the cumulative total of cases reported.
  • New confirmed cases: This is the number of new cases reported on each respective date.
    • For the U.S. and states, a trendline shows the rolling 7-day average of new cases, to help better visualize the peak.
  • Total deaths: This is the cumulative total of deaths reported.
  • New deaths: This is the number of new deaths reported on each respective date.
    • For the U.S. and states, a trendline shows the rolling 7-day average of new deaths, to help better visualize the peak.

Total confirmed cases

U.S.

Our states

Our counties

New confirmed cases

U.S.

Our states

Our counties

Total deaths

U.S.

Our states

Our counties

New deaths

U.S.

Our states

Our counties

Stay-at-home comparisons

• This section is a work in progress. It’s exploring what effect stay-at-home orders have on spread. It’s inherentely messy because some states have localized orders but not orders for their full state and because states implemented the orders at different times.
  • The first plot shows a rolling 3-day average of new cases per million residents, averaged across 2 groups of states – those with a state-wide stay-at-home order in effect and those without. The size of the dots reflect the number of states in each group for each given day (so the dots are getting bigger over time for the group with orders, as more states implement those orders).
    • So far, this view doesn’t show if these orders are “working” or not. Instead, the biggest takeaway from the current plot is that the states that implemented orders are reacting to having worse spread, which is why the case rate is so much higher at the start for them. As a state decides it has a problem and implements an order, it joins the grouping of states with orders and drives the rate up for that group.
    • Over time (if the policies work), what we’d expect is that the line for the group with orders flattens or declines in relation to the no-order group. It also may become moot if all states issue orders.
    • As states start rescending their orders, I’ll put them back into the no-order group, so the no-order group should beging to expand again.
  • The second plot tracks progress of states by the number of days since orders have been in effect. It includes only those states with orders and shows their average new case growth rate (a rolling 3-day average of daily growth rates) based on how long it’s been since the order went into effect. Again, the size of the dots show how many states are included in each point – i.e., as you go further right, the dots are smaller because less states are that far past their order.
    • I’m working on how to add a baseline to this chart to compare to states without orders, but that’s challenging because there’s no way to fully align timing.